Certificate in Business Analytics
(Non-degree)
Certificate Requirements
Students must have previously completed BUSN 240 or equivalent 200-level or higher course in statistics.
Required Courses (12 credit hours)
Complete the following:
In this course students will be introduced to the tools and techniques of business analytics. Students will learn basic programming and advanced applications of software with business applications. By doing so students will increase their fluency in data and mathematical communication. Upon completion of this course students will be ready to take courses on advanced topics in business analytics and complete the Business Analytics Certificate. Prerequisite: A grade of B- or higher in BUSN 240 Business Statistics or an equivalent 200-level or higher course in statistics or MATH 201 or another 200-level or higher math course, can either be taken as a corequisite or a prerequisite.
Students will integrate competencies of business analytics and decision sciences as they influence the world of business. This capstone course is project-based in nature, and students will incorporate components of the business analytics certificate curriculum. Students will engage externally with business and other stakeholders to complete projects using 鈥渄ata to decision making鈥� processes learned throughout their certificate study. The course culminates in a public oral defense of their work. Prerequisites: BUSN 301 Business Analytics: Intro to Business Intelligence and two (2) other Business Analytics courses from the certificate program passed with a B- or better.
Choose two of the following:
A foundational course for the study of computer science and information systems. The course covers an overview of programming methodology and gives the student an ability to write computer programs using standard style and structure. Programming projects are completed in one or more high-level languages. Additional course fee is required. Prerequisite: High school algebra or equivalent.
An introduction to foundational concepts in data science, including: information retrieval and storage, preprocessing, visualization, exploratory data analysis, applied machine learning, research methods, and experimental design. Students will develop solutions to computational problems spanning a variety of disciplines using state-of-the-art scientific programming tools and techniques, with an emphasis on the interpretation and presentation of experimental results. Additional course fee required. Prerequisite: CSIS 201 Introduction to Computer Science I or by instructor permission.
In this course, you will learn to identify, evaluate, and capture business analytic opportunities to create value. You will learn basic analytic methods and be able to analyze case studies on organizations. We will explore the challenges that can arise in starting and using analytics in organizations. The course emphasizes that business analytics is not solely a theoretical discipline: these techniques are used to provide real insights and improve the speed, reliability, and quality of decisions. The concepts learned in this class will help students identify opportunities in which business analytics can be used to improve performance and support important decisions. Prerequisite: A grade of B- or higher in BUSN 301 Intro to Business Intelligence.
This course provides an introduction as well as hands-on experience in Tableau and data visualization. It introduces students to design principles for creating meaningful displays of quantitative and qualitative data to facilitate managerial decision-making. A primary emphasis is placed on storytelling with data and developing competency in Tableau. Prerequisites: A grade of B- or higher in BUSN 301 Intro to Business Intelligence.
This course deals with the application of statistical techniques to the analysis of economic data. Economists, financial analysts and others rely on econometric methods to estimate relationships and forecast employment, income and other trends. This course emphasizes hands-on application of econometric techniques to a variety of publicly available data. Considerable attention will be paid to the nature and sources of economic data and the application of econometric methods to common questions of value to managers and public decision-makers. Prerequisite: A grade of B- or higher in BUSN 301 Business Analytics: Intro to Business Intelligence.